It is our goal to understand how ovarian cancer develops so that we can use these insights to design ways to prevent the disease, develop more sensitive diagnostic procedures, and find better approaches for treatment. The initial phase of such studies requires identification of the genes involved in initiation and manifestation of the disease. This work is severely hampered by the complex features of ovarian cancer including: (i) The frequent late stage of diagnosis which yields predominately advanced tumors for genetic analysis; (ii) the failure to agree as to whether there is a precursor lesion; and (iii) the apparent differences in causality of familial ovarian cancer and sporadic disease. Therefore, we have developed an in vitro model for ovarian cancer. In this system, rat ovarian surface epithelial cells are subjected to growth stimulation in vitro. This repetitious requirement for growth frequently results in malignant transformation and in other cases results in the development of a partially transformed phenotype. The transformed cells and the tumors they produce in syngeneic and xenogeneic hosts have many features characteristic of clinical ovarian cancer. Furthermore, the multiple individual transformants allows the frequency of occurrence of change in expression of individual genes to be determined. This provides an indirect suggestion of causality and hence a basis for the selection of candidates for more detailed analysis. Thus, this model is an ideal starting point for efforts to find the genetic basis for ovarian cancer. We have used this system with RNA differential display to identify a candidate ovarian cancer gene. This gene is tentatively named LOT1 (Lost on transformation 1) based on its lost or decreased expression in five of eight malignantly transformed rat ovarian surface epithelial cell lines. The gene is the template for a 6.4kb mRNA and the sequence of a partial cDNA clone is not related to known genes. In the present application, we propose to: (l) complete the cloning of the cDNA for LOT1, (2) fully develop our effort to identify other genes involved in ovarian cancer, and (3) determine the function of LOT1, and initiate functional studies on other genes which show altered expression at high frequency in transformed ovarian surface epithelial cells. We hypothesize that the results generated as this study progresses will increase our understanding of how clinical ovarian cancer develops.